Eduardo Souza de Cursi Souza de Cursi Uncertainty Quantification with R

Uncertainty Quantification with R

von Eduardo Souza de Cursi

Bayesian Methods

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Beschreibung

This book is a rigorous but practical presentation of the Bayesian techniques of uncertainty quantification, with applications in R. This volume includes mathematical arguments at the level necessary to make the presentation rigorous and the assumptions clearly established, while maintaining a focus on practical applications of Bayesian uncertainty quantification methods. Practical aspects of applied probability are also discussed, making the content accessible to students. The introduction of R allows the reader to solve more complex problems involving a more significant number of variables. Users will be able to use examples laid out in the text to solve medium-sized problems.

The list of topics covered in this volume includes basic Bayesian probabilities, entropy, Bayesian estimation and decision, sequential Bayesian estimation, and numerical methods. Blending theoretical rigor and practical applications, this volume will be of interest to professionals, researchers, graduate and undergraduate students interested in the use of Bayesian uncertainty quantification techniques within the framework of operations research and mathematical programming, for applications in management and planning.


This book is a rigorous but practical presentation of the Bayesian techniques of uncertainty quantification, with applications in R. This volume includes mathematical arguments at the level necessary to make the presentation rigorous and the assumptions clearly established, while maintaining a focus on practical applications of Bayesian uncertainty quantification methods. Practical aspects of applied probability are also discussed, making the content accessible to students. The introduction of R allows the reader to solve more complex problems involving a more significant number of variables. Users will be able to use examples laid out in the text to solve medium-sized problems.

The list of topics covered in this volume includes basic Bayesian probabilities, entropy, Bayesian estimation and decision, sequential Bayesian estimation, and numerical methods. Blending theoretical rigor and practical applications, this volume will be of interest to professionals, researchers, graduate and undergraduate students interested in the use of Bayesian uncertainty quantification techniques within the framework of operations research and mathematical programming, for applications in management and planning.


Presents Bayesian techniques for uncertainty quantification Uses R to solve complex, multivariate problems Emphasizes practical applications of uncertainty quantification techniques for management and planning

Autor*in

Eduardo Souza de Cursi

Themen in »Uncertainty Quantification with R«

uncertainty quantification Bayesian estimation R software Bayesian methods Bayesian Monte Carlo MCMC methods numerical methods game theory reliability

Stimmen zu »Uncertainty Quantification with R«

Details

ISBN: 9783031482076
Verlag: Springer International Publishing
Erscheinung: 07.05.2024

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